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Journal articles on the topic 'Gated Continuous Logic Networks'

Author: Grafiati

Published: 6 September 2023

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1

Boukadida, Souha, Soufien Gdaim, and Abdellatif Mtiba. "Sensor Fault Detection and Isolation Based on Artificial Neural Networks and Fuzzy Logic Applicated on Induction Motor for Electrical Vehicle." International Journal of Power Electronics and Drive Systems (IJPEDS) 8, no. 2 (2017): 601. http://dx.doi.org/10.11591/ijpeds.v8.i2.pp601-611.

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<p>Recently, research has picked up a fervent pace in the area of fault diagnosis of electrical vehicle. Like failures of a position sensor, a voltage sensor, and current sensors. Three-phase induction motors are the “workhorses” of industry and are the most widely used electrical machines. This paper presents a scheme for Fault Detection and Isolation (FDI). The proposed approach is a sensor-based technique using the mains current measurement. Current sensors are widespread in power converters control and in electrical drives. Thus, to ensure continuous operation with reconfiguration co

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Tran, Duc M., Kyungah Kim, and Joon-Young Choi. "CLB-Based Development of BiSS-C Interface Master for Motor Encoders." Electronics 12, no. 4 (2023): 886. http://dx.doi.org/10.3390/electronics12040886.

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Encoder interfaces should be operated in real time with high precision and fast processing for industrial motor control systems. The continuous bidirectional serial synchronous (BiSS-C) interface is an open-source serial communication protocol designed for motor encoders and is suitable for industrial purposes because of its fast serial communication speed. In this study, we propose a method for developing a BiSS-C interface master for a motor encoder slave, using only the configurable logic block (CLB) peripheral integrated into TI microcontroller units. By analyzing the detailed operation pr

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3

KIROLOS, SAMI, and YEHIA MASSOUD. "DYNAMIC VOLTAGE SCALING CONTINUOUS ADAPTIVE-SIZE CELL DESIGN TECHNIQUE." Journal of Circuits, Systems and Computers 17, no. 05 (2008): 871–83. http://dx.doi.org/10.1142/s0218126608004630.

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In this paper, we present an adaptive circuit design that is capable of increasing the effective size-ratio of combinational logic gates to extend the balanced operation in the subthreshold region as well as to maintain high performance at the nominal VDD. We optimize the sizes of the PMOS transistors in the pull-up network for minimum power dissipation and propagation delay over a wide range of supply voltage. In addition to the minimized energy operation, the dynamically adjustable gate size-ratio allows the gate to preserve a symmetric voltage transfer characteristic at both normal supply a

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Plyusnin, Nikolay. "Tunable logic of complex variables and quantum networks on its basis." Robotics and Technical Cybernetics 10, no. 4 (2022): 267–74. http://dx.doi.org/10.31776/rtcj.10404.

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Continuous - additive-multiplicative (AM) logic is considered, in which logical operations are replaced by algebraic operations («×» and «+») or operations with vectors, and binary variables «0» and «1» are replaced by continuous scalar ones («0- 1») or complex variables. To build this logic, a continuous analogue of the canonical form of Boolean logic is used in the form of a perfect disjunctive or conjunctive normal form (KAM logic). A feature of KAM logic is a continuous dependence on input variables and a potential variety of continuous logic functions. Based on the previously proposed «fu

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Li, Zhitao, Yuqian Guo, and Weihua Gui. "Asymptotical feedback controllability of continuous-time probabilistic logic control networks." Nonlinear Analysis: Hybrid Systems 47 (February 2023): 101265. http://dx.doi.org/10.1016/j.nahs.2022.101265.

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6

Yadav, Neetika, Neeta Pandey, and Deva Nand. "Leakage reduction in dual mode logic through gated leakage transistors." Microprocessors and Microsystems 84 (July 2021): 104269. http://dx.doi.org/10.1016/j.micpro.2021.104269.

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7

Chen, Lanlan. "Secure Data Sequence Recognition of All-Optical High-Speed Network Using Semiconductor Optical Amplifier." Journal of Nanoelectronics and Optoelectronics 16, no. 10 (2021): 1667–74. http://dx.doi.org/10.1166/jno.2021.3124.

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Semiconductor optical amplifier (SOA) has nonlinear optical effect and integration advantages, and is widely used in all-optical logic gates. Hence, it is used in the identification of all-optical high-speed network security data sequences. First, the SOA model is established and then simplified based on the existing model. On this basis, the identification model of all-optical high-speed network security data sequence is established, and the concept of integrated turbo-switch is introduced. The structure of the turbo-switch is analyzed. Then, an integrated turbo-switch architecture based on S

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8

Buckley, J. J., and Yoichi Hayashi. "Numerical relationships between neural networks, continuous functions, and fuzzy systems." Fuzzy Sets and Systems 60, no. 1 (1993): 1–8. http://dx.doi.org/10.1016/0165-0114(93)90283-n.

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Csiszár, Orsolya, Gábor Csiszár, and József Dombi. "Interpretable neural networks based on continuous-valued logic and multicriteria decision operators." Knowledge-Based Systems 199 (July 2020): 105972. http://dx.doi.org/10.1016/j.knosys.2020.105972.

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10

Sturlaugson, Liessman, Logan Perreault, and John W. Sheppard. "Factored performance functions and decision making in continuous time Bayesian networks." Journal of Applied Logic 22 (July 2017): 28–45. http://dx.doi.org/10.1016/j.jal.2016.11.030.

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11

Levin, V. I. "Continuous logic and combinatorial problems decision." Journal of Computer and Systems Sciences International 47, no. 3 (2008): 413–21. http://dx.doi.org/10.1134/s1064230708030118.

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12

Tan, Shoutao, Zhanfeng Fang, Yanyi Liu, et al. "An SSD-MobileNet Acceleration Strategy for FPGAs Based on Network Compression and Subgraph Fusion." Forests 14, no. 1 (2022): 53. http://dx.doi.org/10.3390/f14010053.

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Over the last decade, various deep neural network models have achieved great success in image recognition and classification tasks. The vast majority of high-performing deep neural network models have a huge number of parameters and often require sacrificing performance and accuracy when they are deployed on mobile devices with limited area and power consumption. To address this problem, we present an SSD-MobileNet-v1 acceleration method based on network compression and subgraph fusion for Field-Programmable Gate Arrays (FPGAs). Firstly, a regularized pruning algorithm based on sensitivity ana

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ISLAM, MUHAMMAD ASIFUL, C. R. RAMAKRISHNAN, and I. V. RAMAKRISHNAN. "Inference in probabilistic logic programs with continuous random variables." Theory and Practice of Logic Programming 12, no. 4-5 (2012): 505–23. http://dx.doi.org/10.1017/s1471068412000154.

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AbstractProbabilistic Logic Programming (PLP), exemplified by Sato and Kameya's PRISM, Poole's ICL, Raedt et al.'s ProbLog and Vennekens et al.'s LPAD, is aimed at combining statistical and logical knowledge representation and inference. However, the inference techniques used in these works rely on enumerating sets of explanations for a query answer. Consequently, these languages permit very limited use of random variables with continuous distributions. In this paper, we present a symbolic inference procedure that uses constraints and represents sets of explanations without enumeration. This p

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14

PAN, HEPING, and LIN LIU. "FUZZY BAYESIAN NETWORKS — A GENERAL FORMALISM FOR REPRESENTATION, INFERENCE AND LEARNING WITH HYBRID BAYESIAN NETWORKS." International Journal of Pattern Recognition and Artificial Intelligence 14, no. 07 (2000): 941–62. http://dx.doi.org/10.1142/s021800140000060x.

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This paper proposes a general formalism for representation, inference and learning with general hybrid Bayesian networks in which continuous and discrete variables may appear anywhere in a directed acyclic graph. The formalism fuzzifies a hybrid Bayesian network into two alternative forms: the first form replaces each continuous variable in the given directed acyclic graph (DAG) by a partner discrete variable and adds a directed link from the partner discrete variable to the continuous one. The mapping between two variables is not crisp quantization but is approximated (fuzzified) by a conditi

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15

Mojica-Nava, Eduardo, Jimmy Salgado, Duvan Tellez, and Alvaro Lopez. "Optimal Control of Switching Topology Networks." Mathematical Problems in Engineering 2014 (2014): 1–9. http://dx.doi.org/10.1155/2014/268541.

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We present an extension of a previously proposed approach based on the method of moments for solving the optimal control problem for a switching system considering now a continuous external input. This method is based on the transformation of a nonlinear, nonconvex optimal control problem, into an equivalent optimal control problem with linear and convex structure, which allows us to obtain an equivalent convex formulation more appropriate to be solved by high-performance numerical computing. Finally, the design of optimal logic-based controllers for networked systems with a dynamic topology i

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16

Meng, Xiangyu, and Tongwen Chen. "Event-Based Stabilization over Networks with Transmission Delays." Journal of Control Science and Engineering 2012 (2012): 1–8. http://dx.doi.org/10.1155/2012/212035.

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This paper investigates asymptotic stabilization for linear systems over networks based on event-driven communication. A new communication logic is proposed to reduce the feedback effort, which has some advantages over traditional ones with continuous feedback. Considering the effect of time-varying transmission delays, the criteria for the design of both the feedback gain and the event-triggering mechanism are derived to guarantee the stability and performance requirements. Finally, the proposed techniques are illustrated by an inverted pendulum system and a numerical example.

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Alkhayyat, Ahmed, Firas Abedi, Ashish Bagwari, et al. "Fuzzy logic, genetic algorithms, and artificial neural networks applied to cognitive radio networks: A review." International Journal of Distributed Sensor Networks 18, no. 7 (2022): 155013292211135. http://dx.doi.org/10.1177/15501329221113508.

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Cognitive radios are expected to play an important role in capturing the constantly growing traffic interest on remote networks. To improve the usage of the radio range, a cognitive radio hub detects the weather, evaluates the open-air qualities, and then makes certain decisions and distributes the executives’ space assets. The cognitive radio works in tandem with artificial intelligence and artificial intelligence methodologies to provide a flexible and intelligent allocation for continuous production cycles. The purpose is to provide a single source of information in the form of a survey res

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18

Tirian, Gelu-Ovidiu, Ioan Filip, and Gabriela Proştean. "Adaptive control system for continuous steel casting based on neural networks and fuzzy logic." Neurocomputing 125 (February 2014): 236–45. http://dx.doi.org/10.1016/j.neucom.2012.11.052.

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19

Jin, Guangyin, Lingbo Liu, Fuxian Li, and Jincai Huang. "Spatio-Temporal Graph Neural Point Process for Traffic Congestion Event Prediction." Proceedings of the AAAI Conference on Artificial Intelligence 37, no. 12 (2023): 14268–76. http://dx.doi.org/10.1609/aaai.v37i12.26669.

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Traffic congestion event prediction is an important yet challenging task in intelligent transportation systems. Many existing works about traffic prediction integrate various temporal encoders and graph convolution networks (GCNs), called spatio-temporal graph-based neural networks, which focus on predicting dense variables such as flow, speed and demand in time snapshots, but they can hardly forecast the traffic congestion events that are sparsely distributed on the continuous time axis. In recent years, neural point process (NPP) has emerged as an appropriate framework for event prediction i

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20

Qiao, Litao, Weijia Wang, and Bill Lin. "Alternative Formulations of Decision Rule Learning from Neural Networks." Machine Learning and Knowledge Extraction 5, no. 3 (2023): 937–56. http://dx.doi.org/10.3390/make5030049.

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This paper extends recent work on decision rule learning from neural networks for tabular data classification. We propose alternative formulations to trainable Boolean logic operators as neurons with continuous weights, including trainable NAND neurons. These alternative formulations provide uniform treatments to different trainable logic neurons so that they can be uniformly trained, which enables, for example, the direct application of existing sparsity-promoting neural net training techniques like reweighted L1 regularization to derive sparse networks that translate to simpler rules. In add

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21

Levin, V. I. "Continuous logic in problems of finite automata dynamics." Journal of Computer and Systems Sciences International 49, no. 1 (2010): 59–64. http://dx.doi.org/10.1134/s1064230710010077.

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22

Azizan, Farah Liyana, Saratha Sathasivam, Majid Khan Majahar Ali, Nurshazneem Roslan, and Caicai Feng. "Hybridised Network of Fuzzy Logic and a Genetic Algorithm in Solving 3-Satisfiability Hopfield Neural Networks." Axioms 12, no. 3 (2023): 250. http://dx.doi.org/10.3390/axioms12030250.

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This work proposed a new hybridised network of 3-Satisfiability structures that widens the search space and improves the effectiveness of the Hopfield network by utilising fuzzy logic and a metaheuristic algorithm. The proposed method effectively overcomes the downside of the current 3-Satisfiability structure, which uses Boolean logic by creating diversity in the search space. First, we included fuzzy logic into the system to make the bipolar structure change to continuous while keeping its logic structure. Then, a Genetic Algorithm is employed to optimise the solution. Finally, we return the

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23

Bavkar, Dnyaneshwar Madhukar, Ramgopal Kashyap, and Vaishali Khairnar. "Multimodal Sarcasm Detection via Hybrid Classifier with Optimistic Logic." Journal of Telecommunications and Information Technology 3, no. 2022 (2022): 97–114. http://dx.doi.org/10.26636/jtit.2022.161622.

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This work aims to provide a novel multimodal sarcasm detection model that includes four stages: pre-processing, feature extraction, feature level fusion, and classification. The pre-processing uses multimodal data that includes text, video, and audio. Here, text is pre-processed using tokenization and stemming, video is pre-processed during the face detection phase, and audio is pre-processed using the filtering technique. During the feature extraction stage, such text features as TF-IDF, improved bag of visual words, n-gram, and emojis as well on the video features using improved SLBT, and co

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24

Samkov, L. M. "The Logic of mental models in evidence-based medicine." Vrach i informacionnye tehnologii, no. 4 (2020): 78–85. http://dx.doi.org/10.37690/1811-0193-2020-4-78-85.

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The actual task of supplementing intelligent systems of evidence-based medicine with technically implemented mental models is set. Using these models, the user understands the results of digital models in Big Data systems. Clarified concepts related to this issue. The electronic components of neural networks for the implementation of mental models is defined. A variant of continuous logic of mental models is proposed. Functional expressions of convolutions of input signals of artificial neurons are constructed. The basic operations for use in the computational architecture of a neural network

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25

Jiang, Haifeng, Guangzhi Han, He Wang, Xinping Li, and Guopeng Zhang. "Fuzzy-logic-based data-differentiated service supported routing protocol for emergency communication networks in underground mines." International Journal of Distributed Sensor Networks 15, no. 7 (2019): 155014771986476. http://dx.doi.org/10.1177/1550147719864762.

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Hybrid wireless mesh networks are suitable to construct emergency communication networks after disasters in underground mines. The routing decision in emergency scene is more difficult to give an accurate mathematical description due to the constraints of various data types, different data transmission requirements, and multi-parameters. Based on the fuzzy decision theory, this article has proposed a fuzzy-logic-based data-differentiated service supported routing protocol. Through the use of the adaptive fuzzy decision system, fuzzy-logic-based data-differentiated service supported routing pro

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26

Jiang, Yaozhi. "Dialectical Logic K-Model: A Mathematical Model for Machine." Journal of Mathematics Research 9, no. 6 (2017): 82. http://dx.doi.org/10.5539/jmr.v9n6p82.

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An axiom system for dialectical logic K-model which based on Kirchhoff energy-method is established by author in the paper. The author describes that subjective-laws is the mirror imagine reflected from objective-laws and defines that the three-step which named by sensation, abstraction and thinking in artificial intelligence. At same time, describes that axiom system for dialectical logic K-model, in which contains such as logic-variable energy conservation law, Mozi’s principle( mini-max principle) and forbidden law, etc. In the axiom system also contain such as a continuous true-value-funct

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27

Castillo, Oscar, Juan R. Castro, Patricia Melin, and Antonio Rodriguez-Diaz. "Universal Approximation of a Class of Interval Type-2 Fuzzy Neural Networks in Nonlinear Identification." Advances in Fuzzy Systems 2013 (2013): 1–16. http://dx.doi.org/10.1155/2013/136214.

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Neural networks (NNs), type-1 fuzzy logic systems (T1FLSs), and interval type-2 fuzzy logic systems (IT2FLSs) have been shown to be universal approximators, which means that they can approximate any nonlinear continuous function. Recent research shows that embedding an IT2FLS on an NN can be very effective for a wide number of nonlinear complex systems, especially when handling imperfect or incomplete information. In this paper we show, based on the Stone-Weierstrass theorem, that an interval type-2 fuzzy neural network (IT2FNN) is a universal approximator, which uses a set of rules and interv

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Lu, Weijun, Ning Bao, Tangren Zheng, Xiaorui Zhang, and Yutong Song. "Memristor-Based Read/Write Circuit with Stable Continuous Read Operation." Electronics 11, no. 13 (2022): 2018. http://dx.doi.org/10.3390/electronics11132018.

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In recent years, computation-intensive applications, such as artificial intelligence, video processing and encryption, have been developing rapidly. On the other hand, the problems of “storage wall” and “power consumption wall” for the traditional storage and computing separated architectures limit the computing performance. The computational circuits and memory cells based on nonvolatile memristors are unified and become a competitive solution to this problem. However, there are various problems that prevent memristor-based circuits from entering practical applications, one of which is the me

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29

Forti, Stefano. "Trending Topics in Software Engineering (1)." ACM SIGSOFT Software Engineering Notes 47, no. 4 (2022): 6. http://dx.doi.org/10.1145/3561846.3561847.

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The continuous evolution of Software Engineering (SE) comes with a series of methodological and technical challenges to be faced, modelled and suitably tackled. Particularly, we observed that modern software systems are more and more deployed onto pervasive Cloud-IoT networks and composed of heterogeneous distributed components that interact to achieve a common business logic. Such phenomena naturally lead to the continuous development of newly trending topics worth exploring and discussing within our community, spanning the whole lifecycle of software applications (i.e. from design to develop

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30

Jones, Gareth, Chris Lovell, Hywel Morgan, and Klaus-Peter Zauner. "Organising Chemical Reaction Networks in Space and Time with Microfluidics." International Journal of Nanotechnology and Molecular Computation 3, no. 1 (2011): 35–56. http://dx.doi.org/10.4018/jnmc.2011010104.

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Information processing is essential for any lifeform to maintain its organisation despite continuous entropic disturbance. Macromolecules provide the ubiquitous underlying substrate on which nature implements information processing and have also come into focus for technical applications. There are two distinct approaches to the use of molecules for computing. Molecules can be employed to mimic the logic switches of conventional computers or they can be used in a way that exploits the complex functionality offered by a molecular computing substrate. Prerequisite to the latter is a mapping of i

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31

Dembitsky, Nikolay. "Continuum Logic of Control Signals in Analog Cyber–Physical Nets." Inventions 8, no. 4 (2023): 101. http://dx.doi.org/10.3390/inventions8040101.

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The use of embedded processors is the most promising direction in the development of automatic control systems. The article is devoted to analog models and technical solutions that allow continuous analysis of information in a technical system in order to synthesize control signals. Technical solutions are obtained on the basis of continuum logic methods, which aim to increase the speed of embedded computing networks, reduce power consumption, and unify the element base of analog processors. The effect of high speed is achieved due to the transition from sequential digital calculations to para

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32

Bazazzadeh, Mehrdad, and Ali Shahriari. "Enhancing the Performance of Jet Engine Fuel Controller Using Neural Networks." Applied Mechanics and Materials 390 (August 2013): 393–97. http://dx.doi.org/10.4028/www.scientific.net/amm.390.393.

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This paper proposes a fuzzy logic controller for a specific turbojet engine. The turbine engines require control systems to achieve the appropriate performance. The control systems typically featured loops to prevent engine flame out, over speeds, compressor surge, and check turbine inlet temperature limit, either by scheduling the fuel flow during accelerations and decelerations or by controlling the acceleration and deceleration rates of engine spool. This paper presents a successful approach in designing a Fuzzy Logic Controller for a specific Jet Engine. At first a suitable mathematical mo

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33

Oudah, Manal Kadhim, Mohammed Qasim Sulttan, and Salam Waley Shneen. "Fuzzy type 1 PID controllers design for TCP/AQM wireless networks." Indonesian Journal of Electrical Engineering and Computer Science 21, no. 1 (2021): 118. http://dx.doi.org/10.11591/ijeecs.v21.i1.pp118-127.

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<p><span>The search of FLC_PID controller for TCP/AQM Wireless Networks, to deal with congestion for Internet users and to get good performance and capabilities of TCP / IP networks. Neglect of controlling the network delay and the number of continuous users that leads to a problem in the transmission process. Recently, automatic control units are adapted to solve this problem with the difficulty of controlling congestion in the presence of wireless links. This modest research presents one of the traditional PID controller methods with fuzzy logic so that wireless networks and cong

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Divyanshu, Divyanshu, Rajat Kumar, Danial Khan, Selma Amara, and Yehia Massoud. "Design of VGSOT-MTJ-Based Logic Locking for High-Speed Digital Circuits." Electronics 11, no. 21 (2022): 3537. http://dx.doi.org/10.3390/electronics11213537.

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Emerging spintronics devices in recent research have received much interest in various fields. Their unique physical aspects are being explored to keep Moore’s law alive. Therefore, the hardware security aspects of system-on-a-chip (SoC) designs using spintronics devices becomes important. Magnetic tunnel junctions (MTJ) are a potential candidate in spintronics-based devices for beyond-CMOS applications. This work uses voltage-gated spin-orbit torque-assisted magnetic tunnel junction (VGSOT-MTJ) based on the Verilog-A behavioral model to design a possible logic-locking system for hardware secu

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Cheng, Xianrui, Mengyang Sun, and Joshua E. S. Socolar. "Autonomous Boolean modelling of developmental gene regulatory networks." Journal of The Royal Society Interface 10, no. 78 (2013): 20120574. http://dx.doi.org/10.1098/rsif.2012.0574.

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During early embryonic development, a network of regulatory interactions among genes dynamically determines a pattern of differentiated tissues. We show that important timing information associated with the interactions can be faithfully represented in autonomous Boolean models in which binary variables representing expression levels are updated in continuous time, and that such models can provide a direct insight into features that are difficult to extract from ordinary differential equation (ODE) models. As an application, we model the experimentally well-studied network controlling fly body

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Sanober, Sumaya, Deepak Kumar Goyal, Sudhir Keshari, Farrukh Arslan, and Betty Nokobi Dugbakie. "Secure Wireless Networks Based on Fuzzy Logic for Smart HVAC Systems in Small-Scale Industries." Security and Communication Networks 2022 (May 11, 2022): 1–10. http://dx.doi.org/10.1155/2022/3659961.

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The traditional heating, ventilation, and air conditioning (HVAC) system depends on wired mechanical thermostats and regulators deployed at various points in the industrial environment for temperature monitoring. Due to ineffective dynamic changes according to the environment, the traditional HVAC system consumes more electrical energy. Next-generation wireless network (NGWN) systems play a vital role in improving the overall efficiency of the system by continuous monitoring and analysis. A small-scale industry using HVAC systems needs an active smart energy saver technique for maintaining an

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KRASILENKO, VLADIMIR, YURCHUK NATALIYA, and ALEXANDER LAZAREV. "THE NEW BASIC REALIZATIONS OF OPERATIONS “EQUIVALENCE” OF NEURO-FUZZY AND BIOINSPIRED NEURO-LOGICS TO CREATE HARDWARE ACCELERATORS OF ADVANCED EQUIVALENTAL MODELS OF NEURAL STRUCTURES AND MACHINE VISION SYSTEMS." Herald of Khmelnytskyi National University 303, no. 6 (2021): 153–66. http://dx.doi.org/10.31891/2307-5732-2021-303-6-153-166.

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The perspective of neural networks equivalental models (EM) base on vector-matrix procedure with basic operations of continuous and neuro-fuzzy logic (equivalence, absolute difference) are shown. Capacity on base EMs exceeded the amount of neurons in 4-10 times. This is larger than others neural networks paradigms. Amount neurons of this neural networks on base EMs may be 10 – 100 thousand. The base operations in EMs are normalized equivalence operations. The family of new operations “equivalence” and “non-equivalence” of neuro-fuzzy logic’s, which we have elaborated on the based of such gener

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Coqueiro, Thiago, José Jailton, Tássio Carvalho, and Renato Francês. "A Fuzzy Logic System for Vertical Handover and Maximizing Battery Lifetime in Heterogeneous Wireless Multimedia Networks." Wireless Communications and Mobile Computing 2019 (January 10, 2019): 1–13. http://dx.doi.org/10.1155/2019/1213724.

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Bandwidth and power hungry applications are proliferating in mobile networks at a rapid pace. However, mobile devices have been suffering from a lack of sufficient battery capacity for the intensive/continuous use of these applications. In addition, the mobile ecosystem is currently heterogeneous and comprises a plethora of networks with different technologies such as LTE, Wi-Fi, and WiMaX. Hence, an issue must be addressed to ensure that quality of experience (QoE) is provided for the users in this scenario: an energy-efficient strategy that is designed to extend the battery lifetime of mobil

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Gomilanovic, Miljan, Milos Tanasijevic, Sasa Stepanovic, and Filip Miletic. "A Model for Determining Fuzzy Evaluations of Partial Indicators of Availability for High-Capacity Continuous Systems at Coal Open Pits Using a Neuro-Fuzzy Inference System." Energies 16, no. 7 (2023): 2958. http://dx.doi.org/10.3390/en16072958.

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This paper presents a model for determining fuzzy evaluations of partial indicators of the availability of continuous systems at coal open pits using a neuro-fuzzy inference system. The system itself is a combination of fuzzy logic and artificial neural networks. The system availability is divided into partial indicators. By combining the fuzzy logic and artificial neural networks, a model is obtained that has the ability to learn and uses expert judgment for that learning. This paper deals with the ECC system (bucket wheel excavator-conveyor-crushing plant) of the open pit Drmno-Kostolac, whi

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Al-Azzam, Saad, and Ahmad Sharieh. "A data estimation for failing nodes using fuzzy logic with integrated microcontroller in wireless sensor networks." International Journal of Electrical and Computer Engineering (IJECE) 10, no. 4 (2020): 3623. http://dx.doi.org/10.11591/ijece.v10i4.pp3623-3634.

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Continuous data transmission in wireless sensor networks (WSNs) is one of the most important characteristics which makes sensors prone to failure. a backup strategy needs to co-exist with the infrastructure of the network to assure that no data is missing. The proposed system relies on a backup strategy of building a history file that stores all collected data from these nodes. This file is used later on by fuzzy logic to estimate missing data in case of failure. An easily programmable microcontroller unit is equipped with a data storage mechanism used as cost worthy storage media for these da

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KATSIRI, ELEFTHERIA, JEAN BACON, and ALAN MYCROFT. "LINKING TEMPORAL FIRST ORDER LOGIC AND HIDDEN MARKOV MODELS WITH ABSTRACT EVENTS." International Journal on Artificial Intelligence Tools 19, no. 06 (2010): 857–93. http://dx.doi.org/10.1142/s0218213010000443.

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In previous work, we introduced a novel concept of a generalised event, an abstract event, which we define as a change of state of abstract predicates that represent knowledge about the surrounding world. Abstract predicates are defined by formulae in temporal first-order logic (Abstract Event Specification Language (AESL)) whose leaf predicates represent low-level sensor-derived knowledge. Abstract events are detected by Rete Networks structured as a deductive knowledge-base. Current Abstract Event detectors cannot express sufficiently well certain high-level situations, such activity derived

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Hu, Haidai, Kenichi Ataka, Anaïs Menny, et al. "Electrostatics, proton sensor, and networks governing the gating transition in GLIC, a proton-gated pentameric ion channel." Proceedings of the National Academy of Sciences 115, no. 52 (2018): E12172—E12181. http://dx.doi.org/10.1073/pnas.1813378116.

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The pentameric ligand-gated ion channel (pLGIC) from Gloeobacter violaceus (GLIC) has provided insightful structure–function views on the permeation process and the allosteric regulation of the pLGICs family. However, GLIC is activated by pH instead of a neurotransmitter and a clear picture for the gating transition driven by protons is still lacking. We used an electrostatics-based (finite difference Poisson–Boltzmann/Debye–Hückel) method to predict the acidities of all aspartic and glutamic residues in GLIC, both in its active and closed-channel states. Those residues with a predicted pKa cl

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Lombardo, Elia, Moritz Rabe, Yuqing Xiong, et al. "Offline and online LSTM networks for respiratory motion prediction in MR-guided radiotherapy." Physics in Medicine & Biology 67, no. 9 (2022): 095006. http://dx.doi.org/10.1088/1361-6560/ac60b7.

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Abstract Objective. Gated beam delivery is the current clinical practice for respiratory motion compensation in MR-guided radiotherapy, and further research is ongoing to implement tracking. To manage intra-fractional motion using multileaf collimator tracking the total system latency needs to be accounted for in real-time. In this study, long short-term memory (LSTM) networks were optimized for the prediction of superior–inferior tumor centroid positions extracted from clinically acquired 2D cine MRIs. Approach. We used 88 patients treated at the University Hospital of the LMU Munich for trai

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Trottet, Cécile, Thijs Vogels, Kristina Keitel, et al. "Modular Clinical Decision Support Networks (MoDN)—Updatable, interpretable, and portable predictions for evolving clinical environments." PLOS Digital Health 2, no. 7 (2023): e0000108. http://dx.doi.org/10.1371/journal.pdig.0000108.

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Clinical Decision Support Systems (CDSS) have the potential to improve and standardise care with probabilistic guidance. However, many CDSS deploy static, generic rule-based logic, resulting in inequitably distributed accuracy and inconsistent performance in evolving clinical environments. Data-driven models could resolve this issue by updating predictions according to the data collected. However, the size of data required necessitates collaborative learning from analogous CDSS’s, which are often imperfectly interoperable (IIO) or unshareable. We propose Modular Clinical Decision Support Netwo

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Wang, Chengqiang, Xiangqing Zhao, Can Wang, and Zhiwei Lv. "Synchronization of Takagi–Sugeno Fuzzy Time-Delayed Stochastic Bidirectional Associative Memory Neural Networks Driven by Brownian Motion in Pre-Assigned Settling Time." Mathematics 11, no. 17 (2023): 3697. http://dx.doi.org/10.3390/math11173697.

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We are devoted, in this paper, to the study of the pre-assigned-time drive-response synchronization problem for a class of Takagi–Sugeno fuzzy logic-based stochastic bidirectional associative memory neural networks, driven by Brownian motion, with continuous-time delay and (finitely and infinitely) distributed time delay. To achieve the drive-response synchronization between the neural network systems, concerned in this paper, and the corresponding response neural network systems (identical to our concerned neural network systems), we bring forward, based on the structural properties, a class

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Liu, Chunyang, Jiping Liu, Jian Wang, Shenghua Xu, Houzeng Han, and Yang Chen. "An Attention-Based Spatiotemporal Gated Recurrent Unit Network for Point-of-Interest Recommendation." ISPRS International Journal of Geo-Information 8, no. 8 (2019): 355. http://dx.doi.org/10.3390/ijgi8080355.

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Point-of-interest (POI) recommendation is one of the fundamental tasks for location-based social networks (LBSNs). Some existing methods are mostly based on collaborative filtering (CF), Markov chain (MC) and recurrent neural network (RNN). However, it is difficult to capture dynamic user’s preferences using CF based methods. MC based methods suffer from strong independence assumptions. RNN based methods are still in the early stage of incorporating spatiotemporal context information, and the user’s main behavioral intention in the current sequence is not emphasized. To solve these problems, w

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Yotov, Kostadin, Emil Hadzhikolev, Stanka Hadzhikoleva, and Stoyan Cheresharov. "A Method for Extrapolating Continuous Functions by Generating New Training Samples for Feedforward Artificial Neural Networks." Axioms 12, no. 8 (2023): 759. http://dx.doi.org/10.3390/axioms12080759.

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The goal of the present study is to find a method for improving the predictive capabilities of feedforward neural networks in cases where values distant from the input–output sample interval are predicted. This paper proposes an iterative prediction algorithm based on two assumptions. One is that predictions near the statistical sample have much lower error than those distant from the sample. The second is that a neural network can generate additional training samples and use them to train itself in order to get closer to a distant prediction point. This paper presents the results of multiple

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Demeester, Thomas. "System Identification with Time-Aware Neural Sequence Models." Proceedings of the AAAI Conference on Artificial Intelligence 34, no. 04 (2020): 3757–64. http://dx.doi.org/10.1609/aaai.v34i04.5786.

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Established recurrent neural networks are well-suited to solve a wide variety of prediction tasks involving discrete sequences. However, they do not perform as well in the task of dynamical system identification, when dealing with observations from continuous variables that are unevenly sampled in time, for example due to missing observations. We show how such neural sequence models can be adapted to deal with variable step sizes in a natural way. In particular, we introduce a ‘time-aware’ and stationary extension of existing models (including the Gated Recurrent Unit) that allows them to deal

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Kang, Cheng, Xujing Yao, and Daniel Novak. "Fuzzy Windows with Gaussian Processed Labels for Ordinal Image Scoring Tasks." Applied Sciences 13, no. 6 (2023): 4019. http://dx.doi.org/10.3390/app13064019.

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In this paper, we propose a Fuzzy Window with the Gaussian Processed Label (FW-GPL) method to mitigate the overlap problem in the neighboring ordinal category when scoring images. Many published conventional methods treat this challenge as a traditional regression problem and make a strong assumption that each ordinal category owns an adequate intrinsic rank to outline its distribution. Our FW-GPL method aims to refine the ordinal label pattern by using two novel techniques: (1) assembling fuzzy logic to the fully connected layer of convolution neural networks and (2) transforming the ordinal

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CAO, YINGJUN, PAUL P. WANG, and GERMANO RESCONI. "REVERSE ENGINEERING OF THE NK BOOLEAN NETWORK AND ITS EXTENSION — FUZZY LOGIC NETWORK." New Mathematics and Natural Computation 03, no. 01 (2007): 69–87. http://dx.doi.org/10.1142/s179300570700063x.

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In this paper, we first propose a reverse engineering solution to decode the NK Boolean dynamic network given the input and output of the system. This theory utilizes basis functions and dynamic matrices, through which the network's evolutionary behavior can be simulated in a rigorous mathematical manner. Then, a general network model, fuzzy logic network (FLN), is presented as the extension of the Boolean network. This novel network model assigns variable values in a continuous domain, and it can accommodate internal conflicts among variables. In addition, the FLN uses fuzzy logical functions

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